A list of all the figures and tables to go into the biophysical connectivity review paper

Summary of all the data

#get a summary of all the data
summary(data.all)
##     Paper_ID         DOI               Title           Lead_author       
##  Min.   : 1.00   Length:344         Length:344         Length:344        
##  1st Qu.:29.00   Class :character   Class :character   Class :character  
##  Median :57.00   Mode  :character   Mode  :character   Mode  :character  
##  Mean   :46.08                                                           
##  3rd Qu.:60.00                                                           
##  Max.   :78.00                                                           
##                                                                          
##  Institution          Journal            Published     Motivation       
##  Length:344         Length:344         Min.   :2010   Length:344        
##  Class :character   Class :character   1st Qu.:2012   Class :character  
##  Mode  :character   Mode  :character   Median :2014   Mode  :character  
##                                        Mean   :2014                     
##                                        3rd Qu.:2015                     
##                                        Max.   :2016                     
##                                                                         
##  Oceanic_region         Area               Site          
##  Length:344         Length:344         Length:344        
##  Class :character   Class :character   Class :character  
##  Mode  :character   Mode  :character   Mode  :character  
##                                                          
##                                                          
##                                                          
##                                                          
##      Size            Years_total        Date_start      Date_end   
##  Length:344         Min.   :  1.000   Min.   :1960   Min.   :1990  
##  Class :character   1st Qu.:  1.000   1st Qu.:1997   1st Qu.:2001  
##  Mode  :character   Median :  3.000   Median :1997   Median :2003  
##                     Mean   :  8.759   Mean   :2001   Mean   :2008  
##                     3rd Qu.:  5.000   3rd Qu.:2006   3rd Qu.:2009  
##                     Max.   :130.000   Max.   :2070   Max.   :2100  
##                     NA's   :4         NA's   :26     NA's   :26    
##    Run_mode         Yearly_trends_compared Generic_species
##  Length:344         Length:344             Mode :logical  
##  Class :character   Class :character       FALSE:154      
##  Mode  :character   Mode  :character       TRUE :190      
##                                            NA's :0        
##                                                           
##                                                           
##                                                           
##  Multiple_species Species_scientific_name Species_common_name
##  Mode :logical    Length:344              Length:344         
##  FALSE:180        Class :character        Class :character   
##  TRUE :140        Mode  :character        Mode  :character   
##  NA's :24                                                    
##                                                              
##                                                              
##                                                              
##  Species_type       Geographical_zone  Model_reuse      Model_name       
##  Length:344         Length:344         Mode :logical   Length:344        
##  Class :character   Class :character   FALSE:50        Class :character  
##  Mode  :character   Mode  :character   TRUE :293       Mode  :character  
##                                        NA's :1                           
##                                                                          
##                                                                          
##                                                                          
##   Model_type        Model_movement     Physical_model     Nested_submodels
##  Length:344         Length:344         Length:344         Mode :logical   
##  Class :character   Class :character   Class :character   FALSE:307       
##  Mode  :character   Mode  :character   Mode  :character   TRUE :37        
##                                                           NA's :0         
##                                                                           
##                                                                           
##                                                                           
##  Model_resolution_min Model_spatial_shape  Model_depth  
##  Min.   : 0.005       Length:344          Min.   :   6  
##  1st Qu.: 1.850       Class :character    1st Qu.: 100  
##  Median : 4.000       Mode  :character    Median : 500  
##  Mean   : 5.616                           Mean   :1319  
##  3rd Qu.:10.000                           3rd Qu.:4000  
##  Max.   :33.000                           Max.   :6400  
##  NA's   :2                                NA's   :199   
##  Tidal_model_used   Bathymetry_model_used Model_integration 
##  Length:344         Mode :logical         Length:344        
##  Class :character   FALSE:269             Class :character  
##  Mode  :character   TRUE :75              Mode  :character  
##                     NA's :0                                 
##                                                             
##                                                             
##                                                             
##  Model_time_step Model_time_step_type Model_diffusion_scheme
##  Min.   :   50   Length:344           Length:344            
##  1st Qu.:  300   Class :character     Class :character      
##  Median : 3600   Mode  :character     Mode  :character      
##  Mean   : 9567                                              
##  3rd Qu.: 4500                                              
##  Max.   :86400                                              
##  NA's   :181                                                
##  Model_diffusion_direction Model_diffusion_value   PLD_type        
##  Length:344                Min.   :  0.01        Length:344        
##  Class :character          1st Qu.: 50.00        Class :character  
##  Mode  :character          Median : 50.00        Mode  :character  
##                            Mean   : 78.52                          
##                            3rd Qu.: 60.00                          
##                            Max.   :500.00                          
##                            NA's   :160                             
##    PLD_fixed      PLD_variable         PLD_stdev   Spawning_period   
##  Min.   :  2.00   Length:344         Min.   :22    Length:344        
##  1st Qu.: 20.00   Class :character   1st Qu.:22    Class :character  
##  Median : 30.00   Mode  :character   Median :22    Mode  :character  
##  Mean   : 38.19                      Mean   :22                      
##  3rd Qu.: 44.00                      3rd Qu.:22                      
##  Max.   :420.00                      Max.   :22                      
##  NA's   :13                          NA's   :342                     
##  Spawning_interval  Spawning_release_sites Spawning_settlement_sites
##  Length:344         Min.   :    1.0        Min.   :    1            
##  Class :character   1st Qu.:    8.0        1st Qu.:   19            
##  Mode  :character   Median :   40.0        Median :  302            
##                     Mean   :  209.6        Mean   :  600            
##                     3rd Qu.:   61.0        3rd Qu.: 1002            
##                     Max.   :12397.0        Max.   :12397            
##                     NA's   :8              NA's   :38               
##  Spawning_depth_type Spawning_depth_value Spawning_depth_min
##  Length:344          Min.   :  0.00       Min.   :  0.00    
##  Class :character    1st Qu.:  5.00       1st Qu.:  0.00    
##  Mode  :character    Median : 12.50       Median :  0.00    
##                      Mean   : 28.82       Mean   : 17.24    
##                      3rd Qu.: 50.00       3rd Qu.: 10.00    
##                      Max.   :100.00       Max.   :300.00    
##                      NA's   :304          NA's   :270       
##  Spawning_depth_max Spawning_initiation Passive_movement
##  Min.   :  0.20     Length:344          Mode :logical   
##  1st Qu.: 15.00     Class :character    FALSE:91        
##  Median : 22.50     Mode  :character    TRUE :253       
##  Mean   : 59.63                         NA's :0         
##  3rd Qu.: 60.00                                         
##  Max.   :500.00                                         
##  NA's   :270                                            
##  Diel_vertical_migration Circatidal_migration Pynocline_migration
##  Mode :logical           Mode :logical        Mode :logical      
##  FALSE:300               FALSE:338            FALSE:338          
##  TRUE :44                TRUE :6              TRUE :6            
##  NA's :0                 NA's :0              NA's :0            
##                                                                  
##                                                                  
##                                                                  
##  Halocline_migration Ontogentic_vertical_migration
##  Mode :logical       Mode :logical                
##  FALSE:343           FALSE:316                    
##  TRUE :1             TRUE :28                     
##  NA's :0             NA's :0                      
##                                                   
##                                                   
##                                                   
##  Vertical_swimming_ability Horizontal_swimming_ability Sinking_velocity
##  Mode :logical             Mode :logical               Mode :logical   
##  FALSE:339                 FALSE:331                   FALSE:340       
##  TRUE :5                   TRUE :13                    TRUE :4         
##  NA's :0                   NA's :0                     NA's :0         
##                                                                        
##                                                                        
##                                                                        
##  Egg_buoyancy    Mortality       Mortality_rate     Mortality_function
##  Mode :logical   Mode :logical   Length:344         Length:344        
##  FALSE:8         FALSE:204       Class :character   Class :character  
##  TRUE :11        TRUE :140       Mode  :character   Mode  :character  
##  NA's :325       NA's :0                                              
##                                                                       
##                                                                       
##                                                                       
##  Orientation     Orientation_value    Growth        Growth_func       
##  Mode :logical   Length:344         Mode :logical   Length:344        
##  FALSE:335       Class :character   FALSE:321       Class :character  
##  TRUE :9         Mode  :character   TRUE :23        Mode  :character  
##  NA's :0                            NA's :0                           
##                                                                       
##                                                                       
##                                                                       
##  Sensory_ability Sensory_impl       Sensory_extent  
##  Mode :logical   Length:344         Min.   : 1.000  
##  FALSE:143       Class :character   1st Qu.: 5.000  
##  TRUE :201       Mode  :character   Median :10.000  
##  NA's :0                            Mean   : 8.181  
##                                     3rd Qu.:10.000  
##                                     Max.   :50.000  
##                                     NA's   :173     
##  Settlement_competency_window Settlement_competency_type
##  Mode :logical                Length:344                
##  FALSE:167                    Class :character          
##  TRUE :168                    Mode  :character          
##  NA's :9                                                
##                                                         
##                                                         
##                                                         
##  Settlement_competency_factor Settlement_competency_type_start
##  Length:344                   Min.   :  0.0                   
##  Class :character             1st Qu.:  5.0                   
##  Mode  :character             Median :  9.0                   
##                               Mean   : 13.5                   
##                               3rd Qu.: 20.0                   
##                               Max.   :152.0                   
##                               NA's   :177                     
##  Settlement_site_type Settlement_site_size
##  Length:344           Min.   :  0.50      
##  Class :character     1st Qu.:  3.70      
##  Mode  :character     Median :  5.00      
##                       Mean   : 14.83      
##                       3rd Qu.: 11.00      
##                       Max.   :300.00      
##                       NA's   :233         
##  Particles_spawned_at_individual_type Particles_spawned_at_individual_site
##  Length:344                           Min.   :       10                   
##  Class :character                     1st Qu.:      500                   
##  Mode  :character                     Median :     6800                   
##                                       Mean   : 10940204                   
##                                       3rd Qu.:   100000                   
##                                       Max.   :100000000                   
##                                       NA's   :39                          
##  Particles_spawned_range_min Particles_spawned_range_max
##  Min.   :   1                Min.   : 1000              
##  1st Qu.:   1                1st Qu.: 1000              
##  Median : 100                Median : 1400              
##  Mean   :1040                Mean   : 2960              
##  3rd Qu.: 100                3rd Qu.: 1400              
##  Max.   :5000                Max.   :10000              
##  NA's   :339                 NA's   :339                
##  Particles_spawned_super_individual Particles_spawned_period
##  Mode :logical                      Length:344              
##  FALSE:333                          Class :character        
##  TRUE :11                           Mode  :character        
##  NA's :0                                                    
##                                                             
##                                                             
##                                                             
##  Particles_spawned_total Replicated_run  Sensitivity_analysis
##  Min.   :3.280e+02       Mode :logical   Length:344          
##  1st Qu.:6.100e+05       FALSE:337       Class :character    
##  Median :3.200e+06       TRUE :7         Mode  :character    
##  Mean   :6.815e+08       NA's :0                             
##  3rd Qu.:6.100e+07                                           
##  Max.   :6.100e+09                                           
##  NA's   :38                                                  
##  Statistical_methods_used Empirically_validated Dispersal_kernel  
##  Length:344               Mode :logical         Length:344        
##  Class :character         FALSE:269             Class :character  
##  Mode  :character         TRUE :75              Mode  :character  
##                           NA's :0                                 
##                                                                   
##                                                                   
##                                                                   
##  Temporal_kernel Accumulation_kernel Partial_summation
##  Mode :logical   Mode :logical       Mode :logical    
##  FALSE:343       FALSE:343           FALSE:341        
##  TRUE :1         TRUE :1             TRUE :3          
##  NA's :0         NA's :0             NA's :0          
##                                                       
##                                                       
##                                                       
##  Minimum_arrival_time Mean_distance      Median_distance
##  Mode :logical        Length:344         Mode :logical  
##  FALSE:337            Class :character   FALSE:316      
##  TRUE :7              Mode  :character   TRUE :28       
##  NA's :0                                 NA's :0        
##                                                         
##                                                         
##                                                         
##  Distance_travelled_mean Trajectory_travelled_mean
##  Min.   :  9.1           Min.   :171.1            
##  1st Qu.: 34.0           1st Qu.:172.7            
##  Median : 78.2           Median :174.2            
##  Mean   :161.2           Mean   :174.2            
##  3rd Qu.:230.0           3rd Qu.:175.7            
##  Max.   :952.0           Max.   :177.3            
##  NA's   :291             NA's   :342              
##  Distance_travelled_stdev Distance_travelled_median Direction_mean 
##  Length:344               Length:344                Mode :logical  
##  Class :character         Class :character          FALSE:339      
##  Mode  :character         Mode  :character          TRUE :5        
##                                                     NA's :0        
##                                                                    
##                                                                    
##                                                                    
##  Depth_mean      Distance_travelled_upper_quantile Distance_travelled_max
##  Mode :logical   Mode :logical                     Length:344            
##  FALSE:339       FALSE:317                         Class :character      
##  TRUE :5         TRUE :27                          Mode  :character      
##  NA's :0         NA's :0                                                 
##                                                                          
##                                                                          
##                                                                          
##  Distance_travelled_min Biophysical_matrix Travel_time_mean
##  Length:344             Mode :logical      Mode :logical   
##  Class :character       FALSE:341          FALSE:340       
##  Mode  :character       TRUE :3            TRUE :4         
##                         NA's :0            NA's :0         
##                                                            
##                                                            
##                                                            
##     Isotropy      Positive_area    Seeded_area     Centre_of_mass 
##  Min.   :0.0700   Min.   : 50.0   Min.   :0.7260   Mode :logical  
##  1st Qu.:0.0950   1st Qu.: 92.5   1st Qu.:0.7290   FALSE:341      
##  Median :0.3000   Median :135.0   Median :0.7365   TRUE :3        
##  Mean   :0.2386   Mean   :126.3   Mean   :0.7372   NA's :0        
##  3rd Qu.:0.3650   3rd Qu.:164.5   3rd Qu.:0.7448                  
##  Max.   :0.3800   Max.   :194.0   Max.   :0.7500                  
##  NA's   :337      NA's   :341     NA's   :340                     
##  Aggregation_index  Mean_length    Connectance       
##  Min.   :0.3800    Min.   :16.25   Length:344        
##  1st Qu.:0.4025    1st Qu.:16.44   Class :character  
##  Median :0.4250    Median :16.62   Mode  :character  
##  Mean   :0.4250    Mean   :16.62                     
##  3rd Qu.:0.4475    3rd Qu.:16.81                     
##  Max.   :0.4700    Max.   :17.00                     
##  NA's   :342       NA's   :342                       
##  Proportion_sites_settled Connections_total Connected_clusters_total
##  Mode :logical            Mode :logical     Mode :logical           
##  FALSE:335                FALSE:331         FALSE:337               
##  TRUE :9                  TRUE :13          TRUE :7                 
##  NA's :0                  NA's :0           NA's :0                 
##                                                                     
##                                                                     
##                                                                     
##  Connected_clusters_largest_size Cross_shore_connectivity Dispersion_index
##  Mode :logical                   Mode :logical            Mode :logical   
##  FALSE:341                       FALSE:343                FALSE:343       
##  TRUE :3                         TRUE :1                  TRUE :1         
##  NA's :0                         NA's :0                  NA's :0         
##                                                                           
##                                                                           
##                                                                           
##  Connectivity_matrix_potential Connectivity_matrix_realised
##  Length:344                    Mode :logical               
##  Class :character              FALSE:273                   
##  Mode  :character              TRUE :71                    
##                                NA's :0                     
##                                                            
##                                                            
##                                                            
##  Local_retention Local_retention_mean Local_retention_max Self_recruitment
##  Mode :logical   Min.   :0.0000       Min.   :0.130       Mode :logical   
##  FALSE:231       1st Qu.:0.0180       1st Qu.:0.385       FALSE:243       
##  TRUE :113       Median :0.0518       Median :0.695       TRUE :101       
##  NA's :0         Mean   :0.0944       Mean   :0.630       NA's :0         
##                  3rd Qu.:0.1070       3rd Qu.:0.940                       
##                  Max.   :0.3510       Max.   :1.000                       
##                  NA's   :319          NA's   :340                         
##  Self_recruitment_mean Self_recruitment_max Self_recruitment_values
##  Min.   :0.0011        Min.   :0.0400       Length:344             
##  1st Qu.:0.0485        1st Qu.:0.1775       Class :character       
##  Median :0.1090        Median :0.4200       Mode  :character       
##  Mean   :0.2576        Mean   :0.4713                              
##  3rd Qu.:0.4250        3rd Qu.:0.7662                              
##  Max.   :0.9800        Max.   :1.0000                              
##  NA's   :293           NA's   :312                                 
##  Settlement_success Settlement_success_mean Settlement_success_min
##  Mode :logical      Min.   :0.00105         Min.   :0.0010        
##  FALSE:295          1st Qu.:0.06200         1st Qu.:0.0069        
##  TRUE :49           Median :0.17000         Median :0.0275        
##  NA's :0            Mean   :0.24761         Mean   :0.1518        
##                     3rd Qu.:0.41000         3rd Qu.:0.1635        
##                     Max.   :0.80000         Max.   :0.6700        
##                     NA's   :291             NA's   :336           
##  Directional_exchange_rate Export_probability Source_sink_indicies
##  Mode :logical             Mode :logical      Length:344          
##  FALSE:339                 FALSE:341          Class :character    
##  TRUE :5                   TRUE :3            Mode  :character    
##  NA's :0                   NA's :0                                
##                                                                   
##                                                                   
##                                                                   
##  Graph_theory     Survived_%          Comments             X140          
##  Mode :logical   Length:344         Length:344         Length:344        
##  FALSE:226       Class :character   Class :character   Class :character  
##  TRUE :118       Mode  :character   Mode  :character   Mode  :character  
##  NA's :0                                                                 
##                                                                          
##                                                                          
##                                                                          
##      X141               X142               X143          
##  Length:344         Length:344         Length:344        
##  Class :character   Class :character   Class :character  
##  Mode  :character   Mode  :character   Mode  :character  
##                                                          
##                                                          
##                                                          
## 

General summary section

The years the studies were published

data.all <- data.all %>% mutate(movement = 
  Circatidal_migration |
  Pynocline_migration |
  Halocline_migration |
  Ontogentic_vertical_migration |
  Vertical_swimming_ability |
  Horizontal_swimming_ability |
  Sinking_velocity  | 
  Diel_vertical_migration) %>% mutate(settlement = Sensory_extent > 0)

##data.all.comparisons <- data.all %>% gather(Behaviours, Implemented, Passive_movement,movement)

data.all.comparisons <- data.all %>% gather(Behaviours, Implemented,Passive_movement,movement,Orientation,settlement)
data.papers.published <- data.all.comparisons %>% select(Paper_ID,Published,Behaviours,Implemented) %>% distinct(Paper_ID,Published,Behaviours,Implemented)
data.papers.published <- filter(data.papers.published,Implemented == TRUE)
ggplot(data.papers.published, aes(Published)) + geom_bar(aes(fill = Behaviours)) +labs( x = "Publication year", y = "Number of papers")

###Published studies for each model

source("sort_factor.R")
ggplot(data.all,aes(SortFactorBySize(DOI))) + geom_bar() + theme(axis.text.x=element_blank(),
                        axis.ticks.x=element_blank()) + xlab("Individual model runs per study")

###Different taxa

data.taxa <- select(data.all,Species_type) %>% na.omit()
ggplot(data=data.taxa,aes(SortFactorBySize(Species_type))) + geom_bar() + coord_flip() + ylab("Number of models using the taxa") + xlab("Taxa")

Oceangraphic regions

data.regions <- data.all %>% select(Paper_ID,Oceanic_region) %>% distinct(Paper_ID,Oceanic_region)
data.regions %>% group_by(Oceanic_region) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 21 × 3
##        Oceanic_region     n       freq
##                 <chr> <int>      <dbl>
## 1          Baltic Sea     1 0.01369863
## 2          Bering Sea     2 0.02739726
## 3       Carribean Sea     5 0.06849315
## 4              Global     2 0.02739726
## 5  Gulf of California     4 0.05479452
## 6      Gulf of Mexico     5 0.06849315
## 7        Indian Ocean     3 0.04109589
## 8        Indo-Pacific     4 0.05479452
## 9   Mediterranean Sea    11 0.15068493
## 10      North Pacific     1 0.01369863
## # ... with 11 more rows
ggplot(data.regions,aes(SortFactorBySize(Oceanic_region)),fill=gray) + geom_bar() + coord_flip() + xlab("Oceanographic region") + ylab("Number of papers per region")

Biophysical models used

data.models <- data.all %>% select(Paper_ID,Model_name) %>% distinct(Paper_ID,Model_name)
data.models %>% group_by(Model_name) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 24 × 3
##           Model_name     n       freq
##                <chr> <int>      <dbl>
## 1                AFS     1 0.01369863
## 2                 AP     1 0.01369863
## 3             ARIANE     2 0.02739726
## 4   Ayata et al 2010     1 0.01369863
## 5  Baptista/Dietrich     1 0.01369863
## 6                CMS     9 0.12328767
## 7             Connie     2 0.02739726
## 8            Connie2     1 0.01369863
## 9         Delft-PART     1 0.01369863
## 10            DROG3D     1 0.01369863
## # ... with 14 more rows

Physical models

This section compares outputs of the physical models ###Physical models used

data.model.ocean <- data.all %>% select(Paper_ID,Physical_model) %>% distinct(Paper_ID,Physical_model)
data.model.ocean %>% group_by(Physical_model) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 36 × 3
##         Physical_model     n       freq
##                  <chr> <int>      <dbl>
## 1                  AFS     1 0.01369863
## 2            AP (ROMS)     1 0.01369863
## 3               ARDIRC     1 0.01369863
## 4                AVISO     1 0.01369863
## 5                 BRAN     4 0.05479452
## 6               CANOPA     1 0.01369863
## 7  CORSE-400 (MARS-3D)     1 0.01369863
## 8         Delft3D-FLOW     1 0.01369863
## 9         Foreman 2008     1 0.01369863
## 10               FVCOM     1 0.01369863
## # ... with 26 more rows

Timestep

data.papers.timestep <- data.all %>% select(Paper_ID,Model_time_step) %>% distinct(Paper_ID,Model_time_step) %>% na.omit()
ggplot(data.papers.timestep,aes(Model_time_step)) + geom_density() + xlab("Time step (seconds)")

Metrics influence

data.timestamp.sr <- select(data.all,Model_time_step,Self_recruitment_mean) %>% na.omit()
ggplot(data.timestamp.sr,aes(Model_time_step,Self_recruitment_mean)) + geom_point()

data.timestamp.lr <- select(data.all,Model_time_step,Local_retention_mean) %>% na.omit()
ggplot(data.timestamp.lr,aes(Model_time_step,Local_retention_mean)) + geom_point()

data.timestamp.ss <- select(data.all,Model_time_step,Settlement_success_mean)
ggplot(na.omit(data.timestamp.ss),aes(Model_time_step,Settlement_success_mean)) + geom_point()

Model resolution and submodels

data.papers.resolution <- data.all %>% select(Paper_ID,Model_resolution_min,Model_spatial_shape) %>% distinct(Paper_ID,Model_resolution_min,Model_spatial_shape)
data.papers.resolution.grid <- filter(data.papers.resolution,Model_spatial_shape == "Grid")
ggplot(data.papers.resolution.grid,aes(Model_resolution_min)) + geom_density() + xlab("The minimumn model resolution (seconds)")

Self-recruitment

data.resolution.sr <- data.all %>% filter(Model_spatial_shape == "Grid") %>%select(Model_resolution_min,Model_spatial_shape,Self_recruitment_mean,Nested_submodels) %>% na.omit() 
ggplot(data.resolution.sr,aes(Model_resolution_min,Self_recruitment_mean)) + geom_point()

ggplot(data.resolution.sr,aes(Nested_submodels,Self_recruitment_mean)) + geom_boxplot()+ geom_jitter(width = 0.2)

####Local retention

data.resolution.lr <- data.all %>% filter(Model_spatial_shape == "Grid") %>%select(Model_resolution_min,Nested_submodels,Local_retention_mean) %>% na.omit()
ggplot(data.resolution.lr,aes(Model_resolution_min,Local_retention_mean)) + geom_point()

ggplot(data.resolution.lr,aes(Nested_submodels,Local_retention_mean)) + geom_boxplot()+ geom_jitter(width = 0.2)

####Settlement success

data.resolution.ss <- data.all %>% filter(Model_spatial_shape == "Grid") %>%select(Model_resolution_min,Nested_submodels,Settlement_success_mean) %>% na.omit()
ggplot(data.resolution.ss,aes(Model_resolution_min,Settlement_success_mean)) + geom_point() 

ggplot(data.resolution.ss,aes(Nested_submodels,Settlement_success_mean)) + geom_boxplot()+ geom_jitter(width = 0.2)

Biological models

Pelagic larval durations

ggplot(data.all,aes(x=PLD_fixed)) + geom_density()
## Warning: Removed 13 rows containing non-finite values (stat_density).

data.all %>% group_by(PLD_type) %>% summarise (n = n()) %>% mutate(freq = n / sum(n)) %>% na.omit
## # A tibble: 3 × 3
##   PLD_type     n       freq
##      <chr> <int>      <dbl>
## 1     Both    17 0.04941860
## 2    Fixed   302 0.87790698
## 3 Variable    22 0.06395349

Comparisons

data.all.lessoutlier <- filter(data.all,PLD_fixed < 150)

ggplot(data.all.lessoutlier,aes(PLD_fixed,Self_recruitment_mean)) + geom_point() 
## Warning: Removed 280 rows containing missing values (geom_point).

ggplot(data.all.lessoutlier,aes(PLD_fixed,Local_retention_mean)) + geom_point()
## Warning: Removed 304 rows containing missing values (geom_point).

ggplot(data.all.lessoutlier,aes(PLD_fixed,Settlement_success_mean)) + geom_point()
## Warning: Removed 281 rows containing missing values (geom_point).

ggplot(data.all.lessoutlier,aes(PLD_fixed,Distance_travelled_mean)) + geom_point() 
## Warning: Removed 282 rows containing missing values (geom_point).

Mortality

data.all %>% filter(Mortality == TRUE) %>% group_by(Mortality_function) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 7 × 3
##               Mortality_function     n        freq
##                            <chr> <int>       <dbl>
## 1                          Decay    11 0.078571429
## 2                         Linear   115 0.821428571
## 3 Temp / Salinty / Age dependent     2 0.014285714
## 4                    Temperature     7 0.050000000
## 5            Temperature / Depth     1 0.007142857
## 6                        Weibull     3 0.021428571
## 7                           <NA>     1 0.007142857
ggplot(data.all, aes(Mortality, Self_recruitment_mean)) + geom_boxplot() + geom_jitter(width = 0.2)
## Warning: Removed 293 rows containing non-finite values (stat_boxplot).
## Warning: Removed 293 rows containing missing values (geom_point).

ggplot(data.all, aes(Mortality, Local_retention_mean)) + geom_boxplot()+ geom_jitter(width = 0.2)
## Warning: Removed 319 rows containing non-finite values (stat_boxplot).
## Warning: Removed 319 rows containing missing values (geom_point).

ggplot(data.all, aes(Mortality, Settlement_success_mean)) + geom_boxplot()+ geom_jitter(width = 0.2)
## Warning: Removed 291 rows containing non-finite values (stat_boxplot).
## Warning: Removed 291 rows containing missing values (geom_point).

ggplot(data.all, aes(Mortality, Distance_travelled_mean)) + geom_boxplot()+ geom_jitter(width = 0.2)
## Warning: Removed 291 rows containing non-finite values (stat_boxplot).

## Warning: Removed 291 rows containing missing values (geom_point).

Sensory extent

ggplot(data.all,aes(x=Sensory_extent)) + geom_density()
## Warning: Removed 173 rows containing non-finite values (stat_density).

ggplot(data.all,aes(x=Sensory_extent,y=Self_recruitment_mean)) + geom_point()
## Warning: Removed 320 rows containing missing values (geom_point).

ggplot(data.all,aes(x=Sensory_extent,y=Local_retention_mean)) + geom_point()
## Warning: Removed 335 rows containing missing values (geom_point).

ggplot(data.all,aes(x=Sensory_extent,y=Settlement_success_mean)) + geom_point()
## Warning: Removed 331 rows containing missing values (geom_point).

Proportions of implemented behaviours

data.all %>% group_by(Mortality) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 2 × 3
##   Mortality     n      freq
##       <lgl> <int>     <dbl>
## 1     FALSE   204 0.5930233
## 2      TRUE   140 0.4069767
data.all %>% group_by(Growth) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 2 × 3
##   Growth     n       freq
##    <lgl> <int>      <dbl>
## 1  FALSE   321 0.93313953
## 2   TRUE    23 0.06686047
data.all %>% group_by(Sensory_ability) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 2 × 3
##   Sensory_ability     n      freq
##             <lgl> <int>     <dbl>
## 1           FALSE   143 0.4156977
## 2            TRUE   201 0.5843023
data.all %>% group_by(Settlement_competency_window) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 3 × 3
##   Settlement_competency_window     n       freq
##                          <lgl> <int>      <dbl>
## 1                        FALSE   167 0.48546512
## 2                         TRUE   168 0.48837209
## 3                           NA     9 0.02616279
data.all %>% group_by(Orientation) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 2 × 3
##   Orientation     n       freq
##         <lgl> <int>      <dbl>
## 1       FALSE   335 0.97383721
## 2        TRUE     9 0.02616279

Proportions of swimming behaviours for ALL larvae

larvae.swimming <- filter(data.all,Passive_movement==FALSE)
larvae.swimming %>% group_by(Horizontal_swimming_ability) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 2 × 3
##   Horizontal_swimming_ability     n      freq
##                         <lgl> <int>     <dbl>
## 1                       FALSE    80 0.8791209
## 2                        TRUE    11 0.1208791
larvae.swimming %>% group_by(Vertical_swimming_ability) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 2 × 3
##   Vertical_swimming_ability     n       freq
##                       <lgl> <int>      <dbl>
## 1                     FALSE    86 0.94505495
## 2                      TRUE     5 0.05494505
larvae.swimming %>% group_by(Ontogentic_vertical_migration) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 2 × 3
##   Ontogentic_vertical_migration     n      freq
##                           <lgl> <int>     <dbl>
## 1                         FALSE    64 0.7032967
## 2                          TRUE    27 0.2967033
larvae.swimming %>% group_by(Diel_vertical_migration) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 2 × 3
##   Diel_vertical_migration     n      freq
##                     <lgl> <int>     <dbl>
## 1                   FALSE    51 0.5604396
## 2                    TRUE    40 0.4395604
larvae.swimming %>% group_by(Halocline_migration) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 2 × 3
##   Halocline_migration     n       freq
##                 <lgl> <int>      <dbl>
## 1               FALSE    90 0.98901099
## 2                TRUE     1 0.01098901
larvae.swimming %>% group_by(Circatidal_migration) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 2 × 3
##   Circatidal_migration     n       freq
##                  <lgl> <int>      <dbl>
## 1                FALSE    86 0.94505495
## 2                 TRUE     5 0.05494505
larvae.swimming %>% group_by(Pynocline_migration) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 2 × 3
##   Pynocline_migration     n       freq
##                 <lgl> <int>      <dbl>
## 1               FALSE    85 0.93406593
## 2                TRUE     6 0.06593407
larvae.swimming %>% group_by(Sinking_velocity) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 2 × 3
##   Sinking_velocity     n       freq
##              <lgl> <int>      <dbl>
## 1            FALSE    87 0.95604396
## 2             TRUE     4 0.04395604
larvae.swimming %>% group_by(Egg_buoyancy) %>% summarise (n = n()) %>% mutate(freq = n / sum(n))
## # A tibble: 3 × 3
##   Egg_buoyancy     n       freq
##          <lgl> <int>      <dbl>
## 1        FALSE     2 0.02197802
## 2         TRUE     4 0.04395604
## 3           NA    85 0.93406593

Comparisons

Outputs with movement / settlement / orientation

data.compare.metrics <- data.all %>% mutate(settlement = Sensory_extent > 0) %>% mutate(move_orien = movement & Orientation) %>% mutate(orien_settle = Orientation & Sensory_extent > 0) %>% mutate(move_orien_settle = Orientation & Sensory_extent > 0 & movement) %>% mutate(move_settle = Sensory_extent > 0 & movement)
data.compare.metrics <- data.compare.metrics %>% gather(Behaviours, Implemented, Passive_movement,movement,Orientation,settlement,move_orien,orien_settle,move_settle,move_orien_settle) %>% filter(Implemented == TRUE)
ggplot(data.compare.metrics,aes(Behaviours,Self_recruitment_mean)) + geom_boxplot(na.rm = TRUE) + geom_jitter(width=0.2) + coord_flip()
## Warning: Removed 467 rows containing missing values (geom_point).

ggplot(data.compare.metrics,aes(Behaviours,Local_retention_mean)) + geom_boxplot(na.rm = TRUE) + geom_jitter(width=0.2) + coord_flip()
## Warning: Removed 563 rows containing missing values (geom_point).

ggplot(data.compare.metrics,aes(Behaviours,Settlement_success_mean)) + geom_boxplot(na.rm = TRUE) + geom_jitter(width=0.2) + coord_flip()
## Warning: Removed 480 rows containing missing values (geom_point).

Comparisons of different movement methods

data.compare.moving <- data.all %>% gather(movement_factor, implemented,  Circatidal_migration, Pynocline_migration, Halocline_migration, Ontogentic_vertical_migration, Vertical_swimming_ability, Horizontal_swimming_ability, Sinking_velocity, Diel_vertical_migration) %>% filter(implemented == TRUE)
ggplot(data.compare.moving,aes(movement_factor,Self_recruitment_mean)) + geom_boxplot(na.rm = TRUE) + geom_jitter(width=0.2) + coord_flip()
## Warning: Removed 71 rows containing missing values (geom_point).

ggplot(data.compare.moving,aes(movement_factor,Local_retention_mean)) + geom_boxplot(na.rm = TRUE) + geom_jitter(width=0.2) + coord_flip()
## Warning: Removed 97 rows containing missing values (geom_point).

ggplot(data.compare.moving,aes(movement_factor,Settlement_success_mean)) + geom_boxplot(na.rm = TRUE) + geom_jitter(width=0.2) + coord_flip()
## Warning: Removed 68 rows containing missing values (geom_point).

Comparisons of different settlement methods

data.compare.settlement <- data.all %>% mutate(settlement,Sensory_extent > 0)
ggplot(data.compare.settlement,aes(settlement,Self_recruitment_mean)) + geom_boxplot(na.rm = TRUE) + geom_jitter(width=0.2) 
## Warning: Removed 293 rows containing missing values (geom_point).

ggplot(data.compare.settlement,aes(settlement,Local_retention_mean)) + geom_boxplot(na.rm = TRUE) + geom_jitter(width=0.2) 
## Warning: Removed 319 rows containing missing values (geom_point).

ggplot(data.compare.settlement,aes(settlement,Settlement_success_mean)) + geom_boxplot(na.rm = TRUE) + geom_jitter(width=0.2) 
## Warning: Removed 291 rows containing missing values (geom_point).

Comparisons of different sensory extent sizes

ggplot(data.compare.settlement, aes(Sensory_extent,Self_recruitment_mean)) + geom_point()
## Warning: Removed 320 rows containing missing values (geom_point).

ggplot(data.compare.settlement, aes(Sensory_extent,Local_retention_mean)) + geom_point()
## Warning: Removed 335 rows containing missing values (geom_point).

ggplot(data.compare.settlement, aes(Sensory_extent,Settlement_success_mean)) + geom_point()
## Warning: Removed 331 rows containing missing values (geom_point).

Comparisons of different sensory extent sizes

##data.compare.settlement <- mutate(data.compare.settlement,settlement_size = Sensory_extent + Settlement_site_size)
ggplot(data.compare.settlement, aes(Settlement_site_size,Self_recruitment_mean)) + geom_point(aes(colour= factor(settlement)))
## Warning: Removed 315 rows containing missing values (geom_point).

ggplot(data.compare.settlement, aes(Settlement_site_size,Local_retention_mean)) + geom_point(aes(colour= factor(settlement)))
## Warning: Removed 338 rows containing missing values (geom_point).

ggplot(data.compare.settlement, aes(Settlement_site_size,Settlement_success_mean)) + geom_point(aes(colour= factor(settlement)))
## Warning: Removed 305 rows containing missing values (geom_point).